Node-Sensitive Graphs. Three real-world node classification datasets, which include Cora, Citeseer, and Pubmed[1]}, are utilized in our experiments for node-sensitive graph learning. Such datasets are citation networks and have been widely used in graph learning research works as standard benchmarks. Notably, these datasets are undirected and do not have edge features within the graphs. For a fair comparison, in our work, we adopt the same dataset splits used in papers of GCNs[2]} and GATs[3]}.
